OpenClaw Memory Hub

Three-tier memory architecture with automated Dreaming pipeline, three-way synchronization, Active Memory recall, and auto-extraction.

Overview

| Tier | Layer | Technology | Purpose | |------|-------|-----------|---------| | L0 | Runtime Retrieval | memory-core plugin (Ollama bge-m3 → SQLite + sqlite-vec) | Real-time semantic + BM25 hybrid search | | L0 | Cloud Recall | MemOS Cloud plugin (optional) | Cross-device memory capture and recall | | L0 | Active Memory | Built-in OpenClaw plugin | Pre-reply sub-agent memory search + context injection | | L1 | Working Memory | memory/YYYY-MM-DD.md files | Daily summaries, todos, technical notes | | L2 | Long-term Memory | MEMORY.md (read-only base) | Key facts, user profile, permanent decisions |

Automated Pipelines

| Pipeline | Schedule | Description | |----------|----------|-------------| | Dreaming | 03:00 UTC daily | Scan logs → DeepSeek analysis → promote to L2 | | Three-way Sync | 18:00 / 20:00 / 22:00 CST | Cloud ↔ Markdown ↔ Vector alignment | | auto-memory v2 | 18:30 / 22:30 CST | Read MemOS Cloud facts → qwen3 filter + memos-extractor-0.6b → MEMORY.md | | Workspace Cleaner | 19:00 CST | Auto-clean working directory | | REM Backfill | 21:30 CST | Feed short-term recall pipeline (after DeepSeek) | | DeepSeek Analysis | 20:30 CST | Deep historical session analysis → DB | | Wiki Compilation | 21:00 CST (optional) | Extract entities → wiki vault pages |

Memory Flow

agent_end → MemOS Cloud (real-time capture + cloud LLM extraction)
              ↓
        sync-cloud-pull.py (18/20/22 CST)
              ↓
        user_workspace/memos-cloud-cache/ (v1.10: isolated from index)
              ↓
        auto-memory.py → qwen3 filter + memos-extractor-0.6b → MEMORY.md
                                (dual-channel: qwen3 dedup + extractor structured supplement)

before_agent_start → MemOS Cloud recall (with recall_filter: local qwen3:8b)
                  + Active Memory sub-agent
                  + memory-core (bge-m3 + BM25, v1.10: zero dirty chunks)
              ↓
        Layered context injected before reply

Bundled Skills

This package includes two auxiliary skills:

1. cross-platform-writer

Path: skills/cross-platform-writer/ Script: skills/cross-platform-writer/scripts/write_file.py

Replaces OpenClaw's built-in write tool for text file creation. Auto-detects encoding (utf-8/utf-8-sig/gbk), handles BOM, and adapts line endings (CRLF/LF) per platform.

When writing text files: write to temp → run write_file.py → cleanup.

2. auto-memory

Path: skills/auto-memory/ Script: scripts/auto_memory_extract.py

Reads the latest MemOS Cloud synced facts (memos-cloud-YYYY-MM-DD.md), filters noise (system crons, duplicates), and uses local qwen3:8b to extract structured long-term memories into MEMORY.md.

Manual trigger: "提取记忆" / "同步记忆" / "整理记忆" Cron: 18:30 / 22:30 CST (30 18,22 * * *)

Setup

One-command auto-setup

bash scripts/auto-setup.sh

Options

bash scripts/auto-setup.sh --skip-ollama   # Skip Ollama install
bash scripts/auto-setup.sh --skip-memos    # Skip MemOS Cloud
bash scripts/auto-setup.sh --dry-run       # Preview only

Manual setup

See references/setup-guide.md for step-by-step manual configuration.

When to Use

Setting up OpenClaw memory for the first time
Configuring memory-core plugin with local Ollama embedding
Installing MemOS Cloud plugin for cross-device sync
Enabling Active Memory for pre-reply context injection
Setting up auto-memory pipeline for MEMORY.md curation
Installing cross-platform-writer for cross-OS file compatibility
Configuring automatic Dreaming and promotion pipelines
Setting up three-way sync between cloud, files, and vector DB

Plugin Conflicts

❌ subconscious-personality-guardian ↔ memory-core

Incompatible. Both use the same OpenClaw memory slot.

Fix: Disable in openclaw.json:

{
  "plugins": {
    "disabled": ["subconscious-personality-guardian"],
    "deny": ["subconscious-personality-guardian"]
  }
}

✅ memory-core + MemOS Cloud

Compatible — designed to work in layers.

User message → MemOS Cloud (static facts) → memory-core (recent context)

✅ Active Memory + MemOS Cloud + memory-core

Compatible — triple-layer recall.

User message
  → Active Memory sub-agent (searches all memory stores)
  → MemOS Cloud (injects long-term facts & preferences)
  → memory-core (semantic + BM25 hybrid retrieval)
  → Agent receives layered context

✅ auto-memory + MemOS Cloud + memos-extractor

Designed to work together. MemOS captures at agent_end, syncs to local files, then auto-memory reads those files for MEMORY.md curation. v1.10 adds a second channel: memos-extractor-0.6b API (MemOS self-developed model) returns structured facts + preferences, cross-validated against qwen3 output.

Components

1. Memory Plugins (L0)

See references/architecture.md for full configuration.

2. Memory Files (L1 + L2)

~/.openclaw/workspace/
├── memory/
│   ├── YYYY-MM-DD.md          # Daily working memory (auto-indexed)
│   ├── MEMORY_INDEX.md        # Vector BM25 cluster summaries
│   └── .sync-*.json           # Sync state files
├── MEMORY.md                  # Long-term memory base
├── AGENTS.md                  # Runtime context + memory rules
└── user_workspace/
    ├── memos-cloud-cache/         # v1.10: Cloud-pulled memory (isolated from index)
    │   └── memos-cloud-*.md       #     Auto-clean >7 days
    ├── scripts/
    │   ├── auto_memory_extract.py  # auto-memory v2 (dual-channel)
    │   └── sync-*.py               # Sync scripts
    └── skills/
        ├── cross-platform-writer/  # Encoding-safe file writer
        └── auto-memory/            # Auto extraction skill

3. Sync Scripts

Located at user_workspace/scripts/:

sync-cloud-pull.py — Pull from MemOS Cloud → memos-cloud-cache/ (v1.10: isolated from memory/)
sync-cloud-push.py — Push local markdown changes → Cloud (SHA256 diff)
sync-vector-index.py — Vector DB → MEMORY_INDEX.md (FTS5 BM25 clustering)
sync-all.sh — Orchestrator: pull → push → vector-index → cache cleanup (>7d) → reindex
auto_memory_extract.py — auto-memory v2 extraction (dual-channel: qwen3 + memos-extractor)

See references/sync-api.md for MemOS Cloud API details.

File Reference

references/architecture.md — Detailed architecture documentation
references/setup-guide.md — Complete manual setup guide with templates
references/sync-api.md — MemOS Cloud API reference
scripts/auto-setup.sh — One-command interactive setup
scripts/auto_memory_extract.py — auto-memory v2 script
skills/cross-platform-writer/ — Cross-platform text file writer skill
skills/auto-memory/ — Auto memory extraction skill